| Presentation | 2002/10/10 Kernel Machine Ensembles by Parallel Boosting Michiko YAMANA, Hiroyuki NAKAHARA, Massimiliano PONTIL, Shun-ichi AMARI, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose ensembles of kernel machines in which each machine is first trained on bootstrap subsets of a whole dataset and then they are combined so as to optimize objective functions. We study two different types of objective functions inspired by boosting methods, namely the exponential criterion and the maximum likelihood criterion. We also discuss the effect of additional convexity constraints to the generalization of the combination. Experimental results show that our ensemble architecture is competitive with a standard single SVM while the former reduces significantly the computational time of the training algorithm. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | ensemble learning / SVM / exponential criterion / maximum likelihood criterion |
| Paper # | NC2002-52 |
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| Committee | NC |
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| Conference Date | 2002/10/10(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Kernel Machine Ensembles by Parallel Boosting |
| Sub Title (in English) | |
| Keyword(1) | ensemble learning |
| Keyword(2) | SVM |
| Keyword(3) | exponential criterion |
| Keyword(4) | maximum likelihood criterion |
| 1st Author's Name | Michiko YAMANA |
| 1st Author's Affiliation | RIKEN Brain Science Institute() |
| 2nd Author's Name | Hiroyuki NAKAHARA |
| 2nd Author's Affiliation | RIKEN Brain Science Institute |
| 3rd Author's Name | Massimiliano PONTIL |
| 3rd Author's Affiliation | University of Siena |
| 4th Author's Name | Shun-ichi AMARI |
| 4th Author's Affiliation | RIKEN Brain Science Institute |
| Date | 2002/10/10 |
| Paper # | NC2002-52 |
| Volume (vol) | vol.102 |
| Number (no) | 381 |
| Page | pp.pp.- |
| #Pages | 5 |
| Date of Issue | |